Evaluating the Efficacy of Real-Time Connected Vehicle Basic Safety Messages in Mitigating Aberrant Driving Behaviour and Risk of Vehicle Crashes: Preliminary Insights from Highway Scenarios

Authors

  • Nan Zhong School of Electronics and Control Engineering, Chang’an University, Xi’an, China
  • Munish Kumar Gupta Faculty of Mechanical Engineering, Opole University of Technology, Opole, Poland
  • Orest Kochan Measuring Engineering Department, Lviv Polytechnic National University, Lviv, Ukraine
  • Xiangping Cheng Applied Physics and Research Institute, Jiangxi Academy of Science, Nanchang, China

DOI:

https://doi.org/10.5755/j02.eie.35601

Keywords:

Connected vehicles, Basic safety messages, Advanced driver assistant systems, Intelligent vehicles, Artificial intelligence

Abstract

Connected vehicle (CV) technology has revolutionised the intelligent transportation management system by providing new perspectives and opportunities. To further improve risk perception and early warning capabilities in intricate traffic scenarios, a comprehensive field test was conducted within a CV framework. Initially, data for basic safety messages (BSM) were systematically gathered within a real-world vehicle test platform. Subsequently, an innovative approach was introduced that combined multimodal interactive filtering with an advanced vehicle dynamics model to integrate BSM vehicle motion data with observations from roadside units. In addition, a driving condition perception methodology was developed, leveraging rough sets and an enhanced support vector machine (SVM), to identify aberrant driver behaviours and potential driving risks effectively. Furthermore, this study integrated BSM data from various scenarios, including car-following, lane changes, and free driving within the CV environment, to formulate multidimensional driving state sequence patterns for short-term predictions (0.5 s) utilising the long short-term memory (LSTM) model framework. The results demonstrated the effectiveness of the proposed approach in accurately identifying potentially hazardous driving conditions and promptly predicting collision risks. The findings from this research hold substantial promise in advancing road traffic safety management.

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Published

2024-02-20

How to Cite

Zhong, N., Gupta, M. K. ., Kochan, O. ., & Cheng, X. (2024). Evaluating the Efficacy of Real-Time Connected Vehicle Basic Safety Messages in Mitigating Aberrant Driving Behaviour and Risk of Vehicle Crashes: Preliminary Insights from Highway Scenarios. Elektronika Ir Elektrotechnika, 30(1), 56-67. https://doi.org/10.5755/j02.eie.35601

Issue

Section

SYSTEM ENGINEERING, COMPUTER TECHNOLOGY

Funding data